Evaluation of rule interestingness measures in medical knowledge discovery in databases

Artificial Intelligence in Medicine

Volumn 41, Issue 3, 2007, Pages 177-196

  Ohsaki, Miho ^a   Abe, Hidenao ^b   Tsumoto, Shusaku ^b   Yokoi, Hideto ^c   Yamaguchi, Takahira ^d  

^a DOSHISHA UNIVERSITY   (Japan)

^b SHIMANE UNIVERSITY   (Japan)

^c KAGAWA UNIVERSITY HOSPITAL   (Japan)

^d KEIO UNIVERSITY   (Japan)

Author keywords

68T30; 68U35; Clinical data; Data mining; Interestingness; Knowledge discovery in databases; Postprocessing

Indexed keywords

DATA PROCESSING; DATABASE SYSTEMS; DISEASES; EXPERT SYSTEMS;

CLINICAL DATA; INTERESTINGNESS; POSTPROCESSING;

DATA MINING;

ARTICLE; CHI SQUARE TEST; DATA BASE; HEPATITIS; INFORMATION PROCESSING; MEDICAL INFORMATION; MENINGITIS; OUTCOME ASSESSMENT; PRIORITY JOURNAL; RISK FACTOR;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLINICAL MEDICINE; DATABASES, FACTUAL; EVIDENCE-BASED MEDICINE; EXPERT SYSTEMS; HEPATITIS; HUMANS; MENINGITIS; MODELS, THEORETICAL;

EID: 35648950495     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2007.07.005     Document Type: Article

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